Thursday, May 28, 2015

A new paper published in Ocean Science Discussions directly contradicts the claim that "90%" of the alleged "missing heat" from anthropogenic global warming has disappeared into the deep oceans below 2000 meters. This was, according to the authors, the favored excuse (out of more than 70 'excuses' at this point) for the "pause" or "hiatus" of global warming over the past 18+ years. Warming of the deep oceans, however, would cause thermal expansion of the deep oceans and add to sea level rise [called steric sea level rise]. The authors examined several datasets including satellite altimetry, ARGO floats, and the GRACE gravitometer satellites, and find that the thermal expansion of the deep oceans and contribution to sea level rise is "negligible," and thus, there is no evidence that the alleged "missing heat" "trapped" by greenhouse gases has somehow sunken to the deep oceans. In addition, the "missing heat" is also nowhere to be found in the upper oceans, nor the atmosphere (because in reality it was lost to space as increased outgoing IR radiation over the past 62 years). The authors find the sea level budget of total sea level rise is "closed" with "negligible" contribution from the deep ocean, thus no warming or thermal expansion from the "missing heat" in the deep ocean can be accounted for:

"...the sea level budget is closed when using the CCI, AVISO and NOAA data. Hence, in these cases, the deep
ocean (below 2000 meters) contribution is negligible."

Note: see prior Hockey Schtick posts using the GRACE ocean mass + ARGO steric sea level calculation of sea level change described in this paper, as well as this NOAA 2012 calculation of same showing sea level rising at less than half the rate claimed by the IPCCExcerpts, full paper here1 Introduction For the 1993–2010 time span of high-precision satellite altimetry era, the 5th Assessment
Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) reported
that the rate of global mean sea level (GMSL) rise could be explained by the combined
25 effects of land ice melt (50 %), ocean thermal expansion (37 %) and anthropogenic
land water storage decrease (13 %) (Church et al., 2013). Over this period, GMSL rise observed by altimeter satellites amounted 3.2 ± 0.4 mm yr−1
, a value only slightly
higher than the sum of the contributions (amounting to 2.8 ± 0.5 mm yr−1
). Although of
the same order of magnitude as associated uncertainties, the 0.4 mm yr−1
difference
may also reflect missing contributions, e.g., the deep ocean contribution below 700 m
5 depth where the coverage of ocean temperature data before the Argo era is very poor.
Estimating the deep ocean warming is an important issue in the context of the current
pause reported since the early 2000s in global mean air and sea surface temperature
evolution (also called the “hiatus”, e.g., Held, 2013; Trenberth and Fasullo, 2013; Smith,
2013). Different explanations have been proposed to explain the hiatus, ranging from reduced radiative forcing due to prolonged solar minimum, increased aerosols emissions
and small numerous volcanic eruptions, changes in stratospheric water vapor,
and enhanced heat uptake in the deep ocean, either in the Pacific or Atlantic regions
(e.g., Trenberth and Fasullo, 2010, 2013; Hansen et al., 2011; Solomon, 2010; Guemas
et al., 2013; Kosaka and Xie, 2013; Balmaseda et al., 2013a; Watanabe et al.,
15 2013; England et al., 2014; Chen and Tung, 2014). The deep ocean heat uptake is
currently the favored explanation of the hiatus considering that greenhouse gases continue
to accumulate at an increasing rate (Peters et al., 2012) and the Earth’s energy
imbalance at the top of the atmosphere is still in the range 0.5–1 Wm−2
(e.g., Hansen
et al., 2011; Loeb et al., 2012; Trenberth et al., 2014; Allan et al., 2014). However, there are still too few studies dedicated to quantify deep ocean heat uptake. Accurate
observations of sea level rise and its components (ocean thermal expansion and
ocean mass change) can, in principle, help constraining the deep ocean contribution
(e.g., von Schuckmann et al., 2014). In particular satellite altimetry-based GMSL rise
corrected for ocean mass change (for example using GRACE space gravimetry data over the oceans) provides estimate of the total (full depth integrated) ocean thermal
expansion (or equivalently ocean heat content). Since the year 2005, comparison with
observed Argo-based ocean thermal expansion (down to ∼ 2000 m depth) may help
quantifying any deep ocean contribution (below 2000 m). In effect, the sea level budget equation is described as follows: GMSL = Ocean Mass + Steric sea level (0–2000 m)
+ Steric sea level (> 2000m) + data errors (1) Note: see prior Hockey Schtick post using this GRACE ocean mass + ARGO steric sea level calculation of sea level change as well as this NOAA 2012 calculation of same showing sea level rising at less than half the rate claimed by the IPCCThe residual term defined as the difference between observed GMSL and observed
5 estimates of ocean mass and steric sea level down to 2000 m depth (see Eq. 2 below)
includes the deep ocean contribution (called “steric sea level (> 2000 m)”): Residual = GMSL − Ocean mass − Steric sea level (0–2000 m)
= Steric sea level (> 2000m) + data errors (2) Attempts to estimate the deep ocean contribution from the sea level budget approach were performed in two recent studies (Llovel et al., 2014; Dieng et al., 2015). Dieng
et al. (2015) considered two periods (2005–2012 and 2003–2012) which correspond to
the availability of new observing systems for estimating thermal expansion and ocean
mass (nearly full ocean temperature and salinity coverage down to 2000 m from Argo
floats and direct ocean mass measurements from GRACE space gravimetry). Time
15 series of satellite altimetry-based sea level (5 different data sets), thermal expansion (8
different products; integration down to 1500 m) and ocean mass (3 products) components
were analyzed in order to estimate the residual term of Eq. (2). Llovel et al. (2014)
performed a similar study over the 2005–2013 time span but with less data sets. Another
attempt concerning this issue is by von Schuckmann et al. (2014). These studies came up to the same conclusion, i.e., the residual term is contaminated by too
large data errors to provide any robust deep ocean contribution estimate. Here we
build on these previous studies, in particular that from Dieng et al. (2015). We focus
on the 2005–2013 time span corresponding to full Argo coverage and compute the
steric sea level component integrating the data down to 2000 m. We also include in our analysis the new sea level product from ESA Climate Change Initiative (CCI)project
(www.esa-sealevel-cci.org), available up to December 2013. We use the same approach
as in Dieng et al. (2015), i.e., we compute the residual time series. The main objective of the present study is to quantify the contributions of errors coming from
one or several terms of the sea level budget (GMSL, ocean mass, steric sea level) in
the residual time series. This is an important issue to be addressed before trying to
estimate any deep ocean contribution.

Received: 07 April 2015 – Accepted: 22 April 2015 – Published: 13 May 2015Sea level budget over 2005–2013: missing contributions and data errorsH. B. Dieng1, A. Cazenave1, K. von Schuckmann2, M. Ablain3, and B. Meyssignac11Laboratoire d'Etudes en Géophysique et Océanographie Spatiales – Centre National d'Etudes Spatiales (LEGOS – CNES), Toulouse, France2Mediterranean Institute of Oceanography (MIO), Université de Toulon, Toulon, France3Collecte Localisation Satellites (CLS), Ramonville, FranceAbstract. Based on the sea level budget closure approach, this study investigates the residuals between observed global mean sea level (GMSL) and the sum of components (steric sea level and ocean mass) for the period January 2005 to December 2013. The objective is to identify the impact of errors in one or several components of the sea level budget on the residual time series. This is a key issue if we want to constrain missing contributions such as the contribution to sea level rise from the deep ocean (> 2000m). For that purpose, we use several data sets as processed by different groups: six altimetry products for the GMSL, four Argo products plus the ORAS4 ocean reanalysis for the steric sea level and three GRACE-based ocean mass products. We find that over the study time span, the observed trend differences in the residuals of the sea level budget can be as large as ~0.55mm yr−1. These trend differences essentially result from the processing of the altimetry data (e.g., choice the geophysical corrections and method of averaging the along-track altimetry data). At short time scale (from sub-seasonal to multi-annual), residual anomalies are significantly correlated with ocean mass and steric sea level anomalies (depending on the time span), indicating that the residual anomalies are related to errors in both GRACE-based ocean mass and Argo-based steric data. Efforts are needed to reduce these various sources of errors before using the sea level budget approach to estimate missing contributions such as the deep ocean heat content.

While many American parents are angry about the Common Core educational standards and related student assessments in math and English, less attention is being paid to the federally driven green Common Core that is now being rolled out across the country. Under the guise of the first new K-12 science curriculum to be introduced in 15 years, the real goal seems to be to expose students to politically correct climate-change orthodoxy during their formative learning years.

The Next Generation of Science Standards were released in April 2013. Thirteen states and the District of Columbia have adopted them, including my state of New Jersey, which signed on in July 2014 and plans to phase in the new curriculum beginning with the 2016-2017 school year. The standards were designed to provide students with an internationally benchmarked science education.

While publicly billed as the result of a state-led process, the new science standards rely on a framework developed by the Washington, D.C.-based National Research Council. That is the research arm of the National Academy of Sciences that works closely with the federal government on most scientific matters.

All of the National Research Council’s work around global warming proceeds from the initial premise of its 2011 report, “America’s Climate Choices” which states that “climate change is already occurring, is based largely on human activities, and is supported by multiple lines of scientific evidence.” From the council’s perspective, the science of climate change has already been settled. Not surprisingly, global climate change is one of the disciplinary core ideas embedded in the Next Generation of Science Standards, making it required learning for students in grade, middle and high school.

The National Research Council framework for K-12 science education recommends that by the end of Grade 5, students should appreciate that rising average global temperatures will affect the lives of all humans and other organisms on the planet. By Grade 8, students should understand that the release of greenhouse gases from burning fossil fuels is a major factor in global warming. And by Grade 12, students should know that global climate models are very effective in modeling, predicting and managing the current and future impact of climate change. To give one example of the council’s reach, these climate-change learning concepts have been incorporated almost verbatim into the New Jersey Department of Education model science curriculum.

Many of the background materials and classroom resources used by instructors in teaching the new curriculum are sourced from government agencies. For example, the Environmental Protection Agency has an array of ready-to-download climate-change primers for classroom use by teachers, including handouts on the link between carbon dioxide and average global temperatures and tear sheets on the causal relationship between greenhouse-gas emissions and rising sea levels.

Similarly, the National Oceanic and Atmospheric Administration and the Energy Department have their own Climate Literacy & Energy Awareness Network, or Clean, which serves as an online portal for the distribution of digital resources to help educators teach about climate change. One such learning module requires students to measure the size of their family’s carbon footprint and come up with ways to shrink it.

Relying on a climate-change curriculum and teaching materials largely sourced from federal agencies—particularly those of the current ideologically driven administration—raises a number of issues. Along with the undue authoritative weight that such government-produced documents carry in the classroom, most of the work is one-sided and presented in categorical terms, leaving no room for a balanced discussion. Moreover, too much blind trust is placed in the predictive power of long-range computer simulations, despite the weak forecasting track record of most climate models to date.

This is unfortunate because the topic of man-made global warming, properly taught, would present many teachable moments and provide an example of the scientific method in action. Precisely because the science of climate change is still just a theory, discussion would help to build student skills in critical thinking, argumentation and reasoning, which is the stated objective of the new K-12 science standards.

For instance: Why has the planet inconveniently stopped warming since the late 1990s even as carbon dioxide levels have continued to rise? How reliable are historical measurements of average global temperatures and atmospheric carbon dioxide levels when, before the 1950s, much of the data are interpolated from such diverse sources as weather balloons, kites, cloud observations, primordial tree rings and Antarctic ice bubbles?

How statistically significant is a 1.4-degree Fahrenheit increase in average global surface temperatures since 1880 for a 4.6 billion-year-old planet with multiple ecosystems and a surface area of some 200 million square miles? How dangerous is the current level of carbon dioxide in the world’s atmosphere, when 400 parts per million expressed as a percentage of the volume of the atmosphere would equate to only 0.04% or approximately zero?

Employing such a Socratic approach to teaching climate change would likely lead to a rational and thought-provoking classroom debate on the merits of the case. However, that is not the point of this academic exercise—which seems to be to indoctrinate young people by using K-12 educators to establish the same positive political feedback loop around global warming that has existed between the federal government and the nation’s colleges and universities for the past two decades.Mr. Tice works in investment management and is a former Wall Street energy research analyst.

A new paper published in the Journal of Atmospheric and Solar-Terrestrial Physics finds that the quality of Northern Hemisphere temperature data has significantly & monotonically decreased since the year 1969, and that the continued use of 'non-valid' weather stations in calculating Northern Hemisphere average temperatures has created a 'positive bias' and "overestimation of temperatures after including non-valid stations." The paper appears to affirm a number of criticisms of skeptics that station losses, fabricated/infilled data, and positively-biased 'adjustments' to temperature data have created a positive skew to the data and overestimation of warming during the 20th and 21st centuries. Graphs from the paper below show that use of both valid and 'non-valid' station data results in a mean annual Northern Hemisphere temperature over 1C warmer at the end of the record in 2013 as compared to use of 'valid' weather station data exclusively. In addition, the paper shows that use of the sharply decreasing number of stations with valid data produces a huge spike in Northern Hemisphere temperatures around ~2004, which is in sharp contrast to much more comprehensive satellite data showing a 'pause' or even cooling over the same period, further calling into question the quality of even the 'valid' land-based stations (urban heat island effects perhaps?).

"The number of valid weather stations is monotonically decreasing after 1969" is shown by the dashed line, and has resulted in an "overestimation of temperature after including non-valid stations" shown by the solid line, especially a spike in temperature in the early 21st century that is not found in satellite temperature records.

Using temperature data from "valid" stations only, and a base period of 1961-1990, the warmest temperatures were in the first half of the 20th century.

Using a base period of 1800-2013 (including 'non-valid' stations) shows a temperature spike beginning in the early 21st century, but this is not found in the much more accurate and spatially comprehensive satellite records.

"The computed average by using all stations [including invalid stations, dashed line] is always greater than from using only valid [stations, solid line at bottom of chart]. Percentage of valid stations has steadily declined since 1969 [shown in grey shaded area].

Highlights

Define indices for data quality and seasonal bias and use for data evaluation.

•

Compute averages for mean and five point summary plus standard deviations.

•

Indicate a monotonically decreasing data quality after the year 1969.

•

Observe an overestimation of temperature after including non-valid stations.

Abstract

Starting from a set of 6190 meteorological stations we are choosing 6130 of them and only for Northern Hemisphere we are computing average values for absolute annual Mean, Minimum, Q1, Median, Q3,Maximum temperature plus their standard deviations for years 1800–2013, while we use 4887 stations and 389 467 rows of complete yearly data. The data quality and the seasonal bias indices are defined and used in order to evaluate our dataset. After the year 1969 the data quality is monotonically decreasing while the seasonal bias is positive in most of the cases. An Extreme Value Distribution estimation is performed for minimum and maximum values, giving some upper bounds for both of them and indicating a big magnitude for temperature changes. Finally suggestions for improving the quality of meteorological data are presented.

A new paper published in Quaternary Science Reviews finds "strong coherence" between the Asian Monsoon/climate and solar activity proxies during the mid-Holocene from 8,800 to 6,100 years ago.

Using a stalagmite proxy with remarkable resolution of up to 2 years, the paper demonstrates "evidence for a direct sun–climate connection during the early mid-Holocene" with "strong coherence at 200-yr cycle [the de Vries solar cycle], suggesting that solar output was actively involved as a primary contributor" to climate variability and the Asian Monsoon. The authors, "speculate that these centennial-scale AM (Asian Monsoon) changes might be regulated by the positive feedbacks of oceanic/atmospheric interactions to the solar activity under the condition of the retreat of continental ice-sheets."

The author's speculated "positive feedbacks of oceanic/atmospheric interactions to the solar activity" may also represent another solar amplification mechanism by which small changes in solar activity may be amplified to large-scale effects upon climate.

Horizontal axis is thousands of years ago, top 4 graphs are proxies of the Asian Monsoon, curve in 2nd graph is summer solar isolation

d18O is a proxy of precipitation (and temperatures) and correlated to the Asian Monsoon. 14C is a proxy of solar activity. Bottom graph is a wavelet analysis showing a strong periodicity at around 200-years related to the de Vries solar cycle (indicated encircled in red in graph above at around 200 year periodicity).

Highlights

A record of 2-yr-resolution Asian Monsoon variability between 8.8 and 6.1 ka B.P.

•

Persistence of centennial Asian monsoon oscillations during the early mid-Holocene.

•

Evidence for a direct sun–climate connection during the early mid-Holocene.

•

New insights into the interplay of the ice-sheets and the tropical ocean on the AM in the early mid-Holocene.

Abstract

Climate during the early Holocene was highly variable due to the complex interplay of external and internal forcing mechanisms. The relative importance for them on the Asian monsoon (AM) evolution yet remains to be resolved. Here we present two-to six-yr-resolution oxygen isotope (δ18O) records of five stalagmites, four of which are annually-laminated, from Qingtian Cave, central China, revealing detailed AM variability between 10.9 and 6.1 ka BP. Over the contemporaneous periods, the δ18O records agree well with each other at multi-decadal to centennial timescales. When pieced together with the previously published isotopic data from the same cave, the final δ18O record reveals detailed AM variability from the last deglaciation to the mid-Holocene, consistent with other cave records. The most striking feature of the δ18O record is the recurrence of centennial-scale oscillations, especially during the annually-counted period (8.8–6.1 ka BP). Cross-wavelet analyses between the δ18O record and solar proxies show strong coherence at 200-yr cycle, suggesting that solar output was actively involved as a primary contributor. The AM depression at 8.2 ka BP is indistinguishable in amplitude and pattern from a series of weak AM events after 8 ka BP. We speculate that these centennial-scale AM (Asian Monsoon) changes might be regulated by the positive feedbacks of oceanic/atmospheric interactions to the solar activity under the condition of the retreat of continental ice-sheets.

"While the presence of 0.04% CO2 in our atmosphere is essential for life in the biosphere, the notion that such a minor constituent of the atmosphere can control the above forces and [atmospheric] motions is absurd. There is, in fact, not one iota of reliable evidence that it does."

Dr. Martin Hertzberg has a PhD in Physical Chemistry from Stanford, earned his BA degree, cum laude, from the Heights Campus of New York University, and was trained as a meteorologist at the U. S. Naval Postgraduate School. His honors include membership in Phi Beta Kappa, a Meritorious Service Award, a Foreign Visiting Scholar at CNRS in Orleans, France, and a Fulbright Professorship.

Friday, May 22, 2015

A paper published today in Environmental Research Letters finds another potential solar amplification mechanism by which changes in solar UV activity over 11-year solar cycles are amplified to large-scale effects upon climate via modulations of the North Atlantic Oscillation [NAO].

The authors model a mechanism whereby large changes (up to 100%) in solar UV over solar cycles affect heating rates of the upper stratosphere, which in turn affect winds and temperature gradients in the troposphere, and heat storage in North Atlantic Ocean. This results in a lagged effect of 3-4 years in the amplitude of the North Atlantic Oscillation, which in turn affects Arctic sea ice extent, other ocean oscillations, the jet stream, and weather patterns around the globe. The paper corroborates several others demonstrating solar influence upon the NAO, as well as other ocean oscillations.

According to the authors,

Numerous studies have suggested an impact of the 11 year solar cycle on the winter North Atlantic Oscillation (NAO), with an increased tendency for positive [NAO signals to occur at maxima of the solar cycle, and negative NAO signals to occur at minima of the solar cycle]. Climate models have successfully reproduced this solar cycle modulation of the NAO, although the magnitude of the effect is often considerably weaker than implied by observations.

A leading candidate for the mechanism of solar influence is via the impact of ultraviolet radiation variability on heating rates in the tropical upper stratosphere, and consequently on the meridional temperature gradient and zonal winds...On reaching the troposphere this produces a response similar to the winter NAO. Recent analyses of observations have shown that solar cycle–NAO link becomes clearer approximately three years after solar maximum and minimum. Previous modelling studies have been unable to reproduce a lagged response of the observed magnitude.

In this study, the impact of solar cycle on the NAO is investigated using an atmosphere–ocean coupled climate model. We show that the model produces significant NAO responses peaking several years after extrema of the solar cycle, persisting even when the solar forcing becomes neutral. This confirms suggestions of a further component to the solar influence on the NAO beyond direct atmospheric heating and its dynamical response. Analysis of simulated upper ocean temperature anomalies confirms that the North Atlantic Ocean provides the memory of the solar forcing required to produce the lagged NAO response. These results have implications for improving skill in decadal predictions of the European and North American winter climate.

Numerous studies have suggested an impact of the 11 year solar cycle on the winter North Atlantic Oscillation (NAO), with an increased tendency for positive (negative) NAO signals to occur at maxima (minima) of the solar cycle. Climate models have successfully reproduced this solar cycle modulation of the NAO, although the magnitude of the effect is often considerably weaker than implied by observations. A leading candidate for the mechanism of solar influence is via the impact of ultraviolet radiation variability on heating rates in the tropical upper stratosphere, and consequently on the meridional temperature gradient and zonal winds. Model simulations show a zonal mean wind anomaly that migrates polewards and downwards through wave–mean flow interaction. On reaching the troposphere this produces a response similar to the winter NAO. Recent analyses of observations have shown that solar cycle–NAO link becomes clearer approximately three years after solar maximum and minimum. Previous modelling studies have been unable to reproduce a lagged response of the observed magnitude. In this study, the impact of solar cycle on the NAO is investigated using an atmosphere–ocean coupled climate model. Simulations that include climate forcings are performed over the period 1960–2009 for two solar forcing scenarios: constant solar irradiance, and time-varying solar irradiance. We show that the model produces significant NAO responses peaking several years after extrema of the solar cycle, persisting even when the solar forcing becomes neutral. This confirms suggestions of a further component to the solar influence on the NAO beyond direct atmospheric heating and its dynamical response. Analysis of simulated upper ocean temperature anomalies confirms that the North Atlantic Ocean provides the memory of the solar forcing required to produce the lagged NAO response. These results have implications for improving skill in decadal predictions of the European and North American winter climate.

1. Introduction

The variability of the Sun's output influences the heating of the stratosphere via the absorption of ultraviolet (UV) by ozone (Haigh1994, Gray et al 2009). Observational studies of the influence of the 11 year solar cycle show warm temperature anomalies in the equatorial upper stratosphere at solar maximum compared to solar minimum (Frame and Gray 2010, Mitchell et al 2014). Significant changes in the extratropical atmospheric circulation have been linked to these temperature anomalies (Kodera 1995, Kodera and Kuroda 2002), and this is supported by modelling studies (e.g. Matthes et al 2004, 2006, Ineson et al 2011). One of the mechanisms for 'top-down' solar influence (Gray et al 2010) involves equatorial stratospheric warm anomalies at solar maximum which increases the mean meridional temperature gradient, resulting in an increase in the mean Westerly wind in the mid-latitude stratosphere. This positive zonal wind anomaly is then amplified by forcing from planetary waves propagating upwards from the troposphere. Along with meridional advection, this wave feedback causes the poleward and downward migration and amplification of the wind anomaly to the mid- and high-latitude lower stratosphere, where it is able to influence tropospheric circulation. The resulting surface response involves sea-level pressure changes at solar maximum which are very similar to the positive phase of the Arctic Oscillation (AO), with anomalous low pressure over the North Pole bordered by anomalous high pressure in mid-latitudes (Thompson and Wallace 1998). Conversely, at solar minimum, a negative AO response results from reduced stratospheric meridional temperature gradients and the downward and poleward propagation of negative zonal wind anomalies. This top-down mechanism occurs on seasonal timescales since planetary wave propagation in the stratosphere is limited to the winter half-year.

This 'top-down' mechanism cannot explain the recently identified lag of approximately 3 years between solar maximum (minimum) and an increased tendency of a positive (negative) North Atlantic Oscillation (NAO) signal superimposed on the intrinsic year-to-year NAO variability (Gray et al 2013). The ability of the climate system to produce a multi-year lag in the winter NAO response necessitates the persistence of solar signals within the climate system from one winter to the next. Scaife et al (2013) showed that the North Atlantic Ocean is a prime candidate for the source of the lag. Model simulations have demonstrated that the sub-surface North Atlantic Ocean can be influenced by NAO changes related to the internal variability of stratospheric circulation (Reichler et al2012) and changes in multidecadal solar irradiance (Menary and Scaife 2014). On interannual timescales, Scaife et al (2013) presented a mechanism involving coupled atmosphere–ocean feedbacks. The NAO is known to be correlated with a tripole pattern in the North Atlantic sea-surface temperatures (SST), (Visbeck et al 2003), which extends below the surface into the ocean mixed layer. Due to the seasonal cycle in surface heat and turbulent fluxes, the mixed-layer-depth (MLD) is deeper in winter than in summer. This suggests that a winter sub-surface ocean signal, linked to solar variability, could persist by being isolated underneath the shallower summer mixed layer from the modifying influence of surface fluxes from the atmosphere. In autumn, as the summer mixed-layer erodes and the deeper winter mixed layer becomes established, any sub-surface solar signal would reconnect with the surface, giving it the potential to influence the atmosphere. This sequestration and re-emergence of signals from one winter to the next has been shown to operate in other contexts (Alexander et al 1999, Timlin et al 2002, Deser et al 2003, Taws et al 2011), and would give rise to a forcing of the NAO by the ocean (Rodwell and Folland 2002). Hanawa and Sugimoto (2004) identified several regions of re-emergence including areas of the North Atlantic relevant to this study. Scaife et al (2013) argue that a weak solar-related AO/NAO signal could build up over a number of years in the tripole region of the North Atlantic Ocean and feedback onto the atmosphere to produce a peak in the NAO signal after a few years.

Several studies have examined the simulated NAO response to solar forcings. Gray et al (2013) and Mitchell et al (2015) showed that Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations were unable to reproduce the observed NAO response. On the other hand, Ineson et al (2011) were able to simulate a realistic amplitude of the NAO response by imposing a higher level of variability in UV-band irradiance. They reproduced the UV-induced 'top-down' mechanism, connecting the upper-stratosphere and the tropospheric NAO. The simulations from Ineson et al (2011) were further analysed by Scaife et al (2013), who showed that the implied ocean–atmosphere coupling in the model used by Ineson et al (2011) was too weak to produce the observed delay.

In this study we use historical simulations of the period 1960–2009 with CMIP5 evolving forcings to explore the influence of solar variability on the NAO. This is different to the experiments of Ineson et al (2011) which use constant forcings within their solar maximum and solar minimum scenarios. We use two ensembles, the first with solar irradiance held constant and the second with time-varying spectrally resolved solar variability. The difference in response of the ensembles should reveal the influence of the varying solar cycle on the atmosphere and oceans.

Figure 1. (a) Time-series of imposed TSI anomaly (black line), and UV-band irradiance anomaly (dashed blue line) with respect to the 1960–2009 mean. (b) Composites of upper stratospheric zonal mean temperature (dashed red line) and DJF NAO-index (black line) as a function of lag with respect to solar maximum minus solar minimum. The upper stratospheric temperature is calculated as the annual average of the region bounded by 0.5–5 hPa (approximately 40–55 km), and 30 °S–30 °N. The NAO-index is defined as the DJF surface pressure difference between the Azores and Iceland. The points where the NAO-index is significant at the 95% level are highlighted with squares.

We have investigated the NAO response to solar variability using a state-of-the-art atmosphere–ocean coupled model. Historical ensembles for the period 1960–2009 were performed with constant and time-varying solar irradiance. Analysis of the differences between the ensembles was performed to identify solar cycle responses in the atmosphere and ocean. The results demonstrate tropical upper stratospheric heating in response to the imposed UV change at solar maximum compared to solar minimum, and confirm the results of Ineson et al (2011), showing a subsequent surface winter NAO response via a 'top-down' mechanism. The response of the NAO peaks 3–4 years following the extreme phase of the solar cycle. This finding is consistent with a recent re-evaluation of observed responses to the solar cycle (Gray et al2013) which shows the largest NAO signal at a similar lag. The in-phase response of the Aleutian Low is also in agreement with observational analyses.

We diagnose the source of the NAO lag in the model by examining its surface and sub-surface solar responses in the North Atlantic Ocean. We find evidence for amplification of 'top-down' solar-related NAO changes via an ocean feedback over a period of several years, as suggested by Scaife et al (2013). This feedback is analysed by examining solar cycle responses in the different nodes of the North Atlantic tripole SST pattern, as this pattern reflects NAO–ocean coupling. The Northern and Middle nodes of the tripole show temperature responses in the surface and sub-subsurface ocean with a similar lag to the NAO. The Southern node, however, does not show any lag. In the Middle node we find re-emergence of solar signals imprinted on the ocean from the previous winter. By remaining intact below the shallow ocean mixed-layer that forms in summer, these signals can re-emerge in winter and reinforce the 'top-down' forcing of the NAO via coupling with the atmosphere. This mechanism is not evident in the Northern and Southern nodes. The simulated re-emergence in the North Atlantic Ocean causes an accumulation of the solar signal, allowing the NAO to grow over several years. This growth is limited by the reversal of the solar cycle, resulting in a lag approximately equal to one quarter of its period. Although we do not explicitly demonstrate here that the growth in the NAO response arises through feedback from the solar SST signal in the Middle node the existence of this feedback is supported by previous studies (Rodwell and Folland 2002, Timlin et al2002) that show the influence of tripole SSTs on the NAO.

The NAO (Hurrell et al2003) is a key mode of regional climate variability that strongly influences the wintertime weather of Northern Europe and Eastern North America. The ability to reproduce the lagged NAO response to solar forcing in atmosphere–ocean coupled models offers the possibility of increased NAO predictability and hence skill in seasonal forecasts (Scaife et al2014) and decadal forecasts up to a few years ahead (Smith et al2012).

Thursday, May 14, 2015

A new paper published in Quaternary Research reconstructs sea levels of the Persian Gulf over the Holocene (past ~10,000 years) and finds sea levels were more than 1 meter higher than the present during the mid-Holocene from "5290 to 4570 years ago, before falling back to current levels by 1440 to 1170 years ago." The sea level reconstruction shows no correlation to CO2 levels over the Holocene, corroborating many other papers demonstrating CO2 levels do not affect sea levels.

Late Quaternary reflooding of the Persian Gulf climaxed with the mid-Holocene highstand previously variously dated between 6 and 3.4 ka. Examination of the stratigraphic and paleoenvironmental context of a mid-Holocene whale beaching allows us to accurately constrain the timing of the transgressive, highstand and regressive phases of the mid- to late Holocene sea-level highstand in the Persian Gulf. Mid-Holocene transgression of the Gulf surpassed today's sea level by 7100–6890 cal yr BP, attaining a highstand of > 1 m above current sea level shortly after 5290–4570 cal yr BP before falling back to current levels by 1440–1170 cal yr BP. The cetacean beached into an intertidal hardground pond during the transgressive phase (5300–4960 cal yr BP) with continued transgression interring the skeleton in shallow-subtidal sediments. Subsequent relative sea-level fall produced a forced regression with consequent progradation of the coastal system. These new ages refine previously reported timings for the mid- to late Holocene sea-level highstand published for other regions. By so doing, they allow us to constrain the timing of this correlatable global eustatic event more accurately.